Paper Citation Record · LEDGER

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners

As of 12 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 1 inbound Pith citation observation for arXiv:2507.05729.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2507.05729 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:22:47.775913Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:22:44.973395Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-06T19:22:47.889034Z

Reference resolution

37 of 37 outbound references displayed

verified exact1
verified fuzzy31
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8f1d506a-cb47-4aa9-b40e-17fa31d8276b · outbound

This paper cites speech foundation model (SFM).

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners speech foundation model (SFM)

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:53.616344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b39e446c-c82a-4322-9b03-7a42b1e6d871 · outbound

This paper cites Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:22:47.966333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6848fed7-5f2a-4555-bfb6-8757fe083e90 · outbound

This paper cites Monaural SIP Model 3.1.1.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Monaural SIP Model 3.1.1

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:53.374507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7978de04-78fb-4014-9889-6004e1dee7b7 · outbound

This paper cites Code Implementations for Models We used code from the GitHub repository for CPC2 2 to train and test the baseline and our proposed models.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Code Implementations for Models We used code from the GitHub repository for CPC2 2 to train and test the baseline and our proposed models

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:53.199928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation abb4bf81-bfdc-49fb-9c23-936766d514c6 · outbound

This paper cites In the monaural experiments, we used the left channel of input speech data.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners In the monaural experiments, we used the left channel of input speech data

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:52.947810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation bd8befa7-b5bc-4d3d-9433-06ba9112db96 · outbound

This paper cites an unresolved cited work.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:22:52.605893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5b74f2b5-299e-4b88-a5b9-d885f9b0fc25 · outbound

This paper cites Dillon, Hearing Aids , 2nd ed.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Dillon, Hearing Aids , 2nd ed

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:52.325153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1c61dba1-c0b9-43b7-b28e-7559209baad2 · outbound

This paper cites an unresolved cited work.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:22:52.152061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d223d254-17a5-4ce5-92b6-0670dec8adad · outbound

This paper cites Objective Quality and Intelligibility Prediction for Users of Assistive Listening Devices: Advantages and limitations of existing tools,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Objective Quality and Intelligibility Prediction for Users of Assistive Listening Devices: Advantages and limitations of existing tools,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:51.961596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8ee31819-4f3e-41f8-8d51-34e3c7b32bcb · outbound

This paper cites Speech intelligibility prediction based on modulation frequency-selective processing,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Speech intelligibility prediction based on modulation frequency-selective processing,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:51.735716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 72e3b6c1-62d1-4c48-95d7-742e94f34571 · outbound

This paper cites Nonintrusive objective measurement of speech intelligibility: A review of methodology,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Nonintrusive objective measurement of speech intelligibility: A review of methodology,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:51.500305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4fb5318f-4783-4150-89a4-7eb2922b3930 · outbound

This paper cites ASR-based speech intelligibility prediction: A review,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners ASR-based speech intelligibility prediction: A review,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:51.325574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8d893cfb-be32-4888-8e8b-b2fab321c8f5 · outbound

This paper cites Clarity-2021 Challenges: Machine Learning Challenges for Advancing Hearing Aid Pro- cessing,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Clarity-2021 Challenges: Machine Learning Challenges for Advancing Hearing Aid Pro- cessing,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:51.000318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d07567a9-ea12-438c-b3d6-4d88eb37de0d · outbound

This paper cites The 2nd Clar- ity Enhancement Challenge for Hearing Aid Speech Intelligibility Enhancement: Overview and Outcomes,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners The 2nd Clar- ity Enhancement Challenge for Hearing Aid Speech Intelligibility Enhancement: Overview and Outcomes,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:50.806614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 04bb9a64-0fac-4b3f-bd20-e065a94cb7de · outbound

This paper cites The 1st Clarity Prediction Challenge: A ma- chine learning challenge for hearing aid intelligibility prediction,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners The 1st Clarity Prediction Challenge: A ma- chine learning challenge for hearing aid intelligibility prediction,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:50.624570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3c057d8d-7fb6-4176-9d31-c5b9bf0ed53a · outbound

This paper cites The 2nd Clarity Prediction Challenge: A Machine Learning Challenge for Hearing Aid Intel- ligibility Prediction,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners The 2nd Clarity Prediction Challenge: A Machine Learning Challenge for Hearing Aid Intel- ligibility Prediction,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:50.382567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9abfb6e3-97fb-4133-94f4-493d51604e8c · outbound

This paper cites Temporal-hierarchical features from noise-robust speech foundation models for non-intrusive intelligi- bility prediction,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Temporal-hierarchical features from noise-robust speech foundation models for non-intrusive intelligi- bility prediction,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:50.267978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5a1c2bbe-dc1f-431b-bcdc-59e1b5a6fbb9 · outbound

This paper cites Attention is All you Need,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Attention is All you Need,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:50.133971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ac687549-46e1-44fe-a6a3-79d5849eca00 · outbound

This paper cites Robust Speech Recognition via Large-Scale Weak Supervision.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Robust Speech Recognition via Large-Scale Weak Supervision

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T19:22:46.219396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e06d3d61-4ec4-48b8-9f95-6031d825dc69 · outbound

This paper cites WavLM: Large- Scale Self-Supervised Pre-Training for Full Stack Speech Pro- cessing,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners WavLM: Large- Scale Self-Supervised Pre-Training for Full Stack Speech Pro- cessing,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:49.997621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 400eee81-2c9e-44da-98f4-b7ffcf205fb7 · outbound

This paper cites The Hearing-Aid Speech Percep- tion Index (HASPI) Version 2,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners The Hearing-Aid Speech Percep- tion Index (HASPI) Version 2,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T19:22:46.403030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dfcb348c-6e2d-4a58-9b37-7419716bc88b · outbound

This paper cites Unsupervised Uncertainty Mea- sures of Automatic Speech Recognition for Non-intrusive Speech Intelligibility Prediction,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Unsupervised Uncertainty Mea- sures of Automatic Speech Recognition for Non-intrusive Speech Intelligibility Prediction,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:49.888550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1a3db557-0f43-49d8-9f6e-0148949bcb7a · outbound

This paper cites MBI-Net: A Non-Intrusive Multi-Branched Speech Intelligibil- ity Prediction Model for Hearing Aids,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners MBI-Net: A Non-Intrusive Multi-Branched Speech Intelligibil- ity Prediction Model for Hearing Aids,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:49.722413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 41429cb3-f0b3-408c-9690-bd8c7d4b3da4 · outbound

This paper cites Speech Foundation Models on In- telligibility Prediction for Hearing-Impaired Listeners,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Speech Foundation Models on In- telligibility Prediction for Hearing-Impaired Listeners,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:49.600366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c9d8328e-dc39-42d3-a31a-3f1f0b8ee8d8 · outbound

This paper cites Non-Intrusive Speech Intelligibility Prediction for Hearing-Impaired Users Using Intermediate ASR Features and Human Memory Models,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Non-Intrusive Speech Intelligibility Prediction for Hearing-Impaired Users Using Intermediate ASR Features and Human Memory Models,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:49.491634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0b3c02d4-0a2a-4b07-9e98-637943872867 · outbound

This paper cites Non-Intrusive Speech Intelligibility Prediction for Hearing Aids using Whisper and Metadata,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Non-Intrusive Speech Intelligibility Prediction for Hearing Aids using Whisper and Metadata,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:49.358694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c48d2020-01ef-4290-97de-c1ac204a89de · outbound

This paper cites Mamba: Linear-time sequence modeling with selective state spaces,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Mamba: Linear-time sequence modeling with selective state spaces,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:49.237425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ba977cfb-1132-4b45-9b1a-05d6518ef402 · outbound

This paper cites Exploring the Ca- pability of Mamba in Speech Applications,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Exploring the Ca- pability of Mamba in Speech Applications,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:49.107908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation be10555e-0a4b-415b-bdd5-8aaa218e111d · outbound

This paper cites On the Parameteriza- tion and Initialization of Diagonal State Space Models,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners On the Parameteriza- tion and Initialization of Diagonal State Space Models,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:49.011100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f65d4304-d540-4ff1-bd9a-e8af40213c30 · outbound

This paper cites Simplified State Space Layers for Sequence Modeling,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Simplified State Space Layers for Sequence Modeling,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:48.874690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 183392c0-967c-457b-be3e-6a528a660b9e · outbound

This paper cites Prefix Sums and Their Applications,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Prefix Sums and Their Applications,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:48.745008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ae642ea7-cfb5-40fe-99b1-e7253497773e · outbound

This paper cites Hungry Hungry Hippos: Towards Language Modeling with State Space Models,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Hungry Hungry Hippos: Towards Language Modeling with State Space Models,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:48.602759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 60cc730d-da2c-40ab-9bd7-11a9e628255d · outbound

This paper cites Whisper-AT: Noise-Robust Automatic Speech Recognizers are Also Strong General Audio Event Taggers,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Whisper-AT: Noise-Robust Automatic Speech Recognizers are Also Strong General Audio Event Taggers,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:48.498082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7fed94b1-2a37-42a8-a228-dd45f33a1825 · outbound

This paper cites Dropout: A Simple Way to Prevent Neural Networks from Overfitting,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Dropout: A Simple Way to Prevent Neural Networks from Overfitting,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:48.389781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 36226636-2206-49bb-b4df-2f36b45b467a · outbound

This paper cites Long short-term memory,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Long short-term memory,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T19:22:47.666953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b924c25-8bf0-4c04-8ba3-7ebaf4f2808b · outbound

This paper cites Adam: A Method for Stochastic Op- timization,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners Adam: A Method for Stochastic Op- timization,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:48.234205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d938d012-6f15-455c-a9ff-369172719d85 · outbound

This paper cites The roles of temporal envelope and fine struc- ture information in auditory perception,.

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners The roles of temporal envelope and fine struc- ture information in auditory perception,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:48.083442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

Observation b39e446c-c82a-4322-9b03-7a42b1e6d871 · inbound